I'm trying to predict the effect different regimetypes have on the likelihood of civil war onset. For this purpose I'm using xtlogit since my dependent variable (onset) is binary and the dataset is paneldata. Seeing that I want to compare different regression models I'll use the
. In one of the robustness models I substitute onset with another binary variable: governmental civil war onset (in danish regering). The problem is that the p-values change when I convert odds ratio to predicted probability using
. For category 3 (liberal democracy) the result is insignificant in the model using odds ratio (p-value = 0,068), however it becomes significant when using predicted probability (p-value = 0,009). How should I interpret this?
Code:
margins, dydx(*)
Code:
margins, dydx(*)
Code:
xtlogit regering i.v2x_regime_lag cgdppc_lag max_rdiscl_lag NHIxl_lag cinc_lag Total_Oil_Income_PC_lag peace_year_lag decay_function_lag Americas Eu > rope MENA Asia if e2==1, or vce(cluster land) Fitting comparison model: Iteration 0: log pseudolikelihood = -665.12183 Iteration 1: log pseudolikelihood = -638.6753 Iteration 2: log pseudolikelihood = -631.36206 Iteration 3: log pseudolikelihood = -631.07399 Iteration 4: log pseudolikelihood = -631.07151 Iteration 5: log pseudolikelihood = -631.07151 Fitting full model: tau = 0.0 log pseudolikelihood = -631.07151 tau = 0.1 log pseudolikelihood = -631.45035 Iteration 0: log pseudolikelihood = -631.45035 Iteration 1: log pseudolikelihood = -631.07129 Iteration 2: log pseudolikelihood = -631.03574 Iteration 3: log pseudolikelihood = -631.03068 Iteration 4: log pseudolikelihood = -631.03059 Iteration 5: log pseudolikelihood = -631.03059 Calculating robust standard errors: Random-effects logistic regression Number of obs = 6,724 Group variable: land Number of groups = 152 Random effects u_i ~ Gaussian Obs per group: min = 12 avg = 44.2 max = 59 Integration method: mvaghermite Integration pts. = 12 Wald chi2(14) = 41.50 Log pseudolikelihood = -631.03059 Prob > chi2 = 0.0001 (Std. Err. adjusted for 152 clusters in land) Robust regering Odds Ratio Std. Err. z P>z [95% Conf. Interval] v2x_regime_lag 1 1.703123 .3962947 2.29 0.022 1.0794 2.687259 2 .9463097 .3586698 -0.15 0.884 .450206 1.989094 3 .3185905 .1997512 -1.82 0.068 .0932273 1.088736 cgdppc_lag .9999647 .0000271 -1.30 0.193 .9999116 1.000018 max_rdiscl_lag 1.904016 .8477297 1.45 0.148 .7955879 4.556728 NHIxl_lag 1.16897 .2459818 0.74 0.458 .773906 1.765706 cinc_lag 4.461662 18.04084 0.37 0.711 .001613 12341.03 Total_Oil_Income_PC_lag 1.000036 .0000525 0.68 0.496 .9999328 1.000139 peace_year_lag .9962825 .0109373 -0.34 0.734 .9750748 1.017952 decay_function_lag .7267845 .2485084 -0.93 0.351 .3718395 1.420547 Americas 1.16026 .2638379 0.65 0.513 .7430119 1.811818 Europe .4185222 .1848075 -1.97 0.049 .1761376 .9944544 MENA 1.619499 .496078 1.57 0.116 .8884728 2.952005 Asia .9230862 .2319049 -0.32 0.750 .5641529 1.510385 _cons .0200784 .0079414 -9.88 0.000 .0092482 .043591 /lnsig2u -3.245333 3.175614 -9.469423 2.978756 sigma_u .1973717 .3133882 .008785 4.434337 rho .0117025 .0367277 .0000235 .8566707 Note: Estimates are transformed only in the first equation. Note: _cons estimates baseline odds (conditional on zero random effects).
Code:
. margins, dydx(*) Average marginal effects Number of obs = 6,724 Model VCE : Robust Expression : Pr(regering=1), predict(pr) dy/dx w.r.t. : 1.v2x_regime_lag 2.v2x_regime_lag 3.v2x_regime_lag cgdppc_lag max_rdiscl_lag NHIxl_lag cinc_lag Total_Oil_Income_PC_lag peace_year_lag decay_function_lag Americas Europe MENA Asia Delta-method dy/dx Std. Err. z P>z [95% Conf. Interval] v2x_regime_lag 1 .0118224 .0052635 2.25 0.025 .001506 .0221387 2 -.000918 .0062151 -0.15 0.883 -.0130994 .0112634 3 -.0118171 .0045169 -2.62 0.009 -.0206701 -.0029641 cgdppc_lag -6.92e-07 5.29e-07 -1.31 0.191 -1.73e-06 3.44e-07 max_rdiscl_lag .0126371 .0088414 1.43 0.153 -.0046916 .0299659 NHIxl_lag .0030637 .0041095 0.75 0.456 -.0049907 .0111182 cinc_lag .029348 .0798936 0.37 0.713 -.1272406 .1859366 Total_Oil_Income_PC_lag 7.01e-07 1.02e-06 0.69 0.491 -1.29e-06 2.70e-06 peace_year_lag -.0000731 .0002163 -0.34 0.735 -.000497 .0003508 decay_function_lag -.0062625 .0067008 -0.93 0.350 -.0193958 .0068708 Americas .002917 .0044431 0.66 0.511 -.0057913 .0116252 Europe -.0170929 .008703 -1.96 0.050 -.0341505 -.0000353 MENA .009461 .0062125 1.52 0.128 -.0027153 .0216373 Asia -.0015706 .004936 -0.32 0.750 -.011245 .0081039 Note: dy/dx for factor levels is the discrete change from the base level.
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